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Probability and Partial Differential Equations in Modern Applied Mathematics

  • Book
  • © 2005

Overview

  • Original contributions by researchers with a common interest in the problems, but
  • with diverse mathematical expertise and perspective

Part of the book series: The IMA Volumes in Mathematics and its Applications (IMA, volume 140)

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Table of contents (16 chapters)

Keywords

About this book

"Probability and Partial Differential Equations in Modern Applied Mathematics" is devoted to the role of probabilistic methods in modern applied mathematics from the perspectives of both a tool for analysis and as a tool in modeling. There is a recognition in the applied mathematics research community that stochastic methods are playing an increasingly prominent role in the formulation and analysis of diverse problems of contemporary interest in the sciences and engineering. A probabilistic representation of solutions to partial differential equations that arise as deterministic models allows one to exploit the power of stochastic calculus and probabilistic limit theory in the analysis of deterministic problems, as well as to offer new perspectives on the phenomena for modeling purposes. There is also a growing appreciation of the role for the inclusion of stochastic effects in the modeling of complex systems. This has led to interesting new mathematical problems at the interface of probability, dynamical systems, numerical analysis, and partial differential equations.

This volume will be useful to researchers and graduate students interested in probabilistic methods, dynamical systems approaches and numerical analysis for mathematical modeling in the sciences and engineering.

Editors and Affiliations

  • Department of Mathematics, Oregon State University, Covallis, USA

    Edward C. Waymire

  • Department of Applied Mathematics, Illionis Institute of Technology, Chicago, USA

    Jinqiao Duan

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